http://www.youtube.com/watch?v=5ymxLA5oRYI

I know that raw data needs to be scrubbed & cleaned up, but in my experience you hold onto it in case there are questions down the road. It is useful, for purposes of replication, to know how the researchers cleaned up the data. The only data to be used now is the scrubbed data, which should return the same results, but it appears the models can’t even do that.

The original data is gone; the models are poorly coded and undocumented; they want governments around the world to spend trillions; and they cannot confirm the hypothesis.

So we now have a large group of scientists who claim that human activity is “unequivocally” causing the planet to get warmer, but the fundamental information used to make this claim is no longer available to them or to other scientists.

I am getting ready to turn up my laugh volume to 11.

And clearly such things as the En Nino and other such perturbations have been modeled in themselves … and predicted with some degree of accuracy. Why do you say the GC models don’t include this? be specific now.

You’re the one that says the GC models don’t include this. Out with it.

oops, missed quoting this last time…

You’re the one saying the models do include it. Burden of proof is on you, dude.

What “current trend”? Once again, cherry picking years does not a trend make. And the models recognise solar cycles but don’t attempt to predict deviations in such (as in the extended current solar lull). And how do the deviations “invalidate” the model? Such may indicate that the model is not complete, but that’s a far cry from “invalid”.

Shall we say, then, casts serious doubt? See below on predictive vs sensitivity. If they are predictive, then a 10 year period of significant error invalidates them. If they are measuring sensitivity, then it casts doubt on that sensitivity measurement.

Yes. You said that certain models (whose outcomes you apparently don’t agree with) should be scorned.

Yes – specifically, long term global climate models should not be trusted, because they fail to model many critical parameters, and cannot be calibrated (see below).

As for “chaos”, you’ve been reading a bit too much fluff. It is true that chaotic behaviour does make it harder and harder to extend FEM models of weather farther and farther into the future at the sub-macro level, but to invalidate the global models, you’d have to establish that such systems are beset by chaotic behaviour as well … and that this chaotic behaviour cannot be quantified and predicted (one of the more interesting results in chaos theory is that what looks totally unpredictable at first blush often shows a quite startling order). Have you done this? If so, where it it published?

Speaking of too much fluff… it is well established that global *weather* is chaotic. That’s global, not local. So much for your “global” assertion. While it is true that a chaotic system can still yield predictions, the chaotic nature greatly reduces the accuracy of predictions that can be made, and reduces the way in which they can be made. Would you care to show me a reference that proves that climate is not chaotic, and that the chaos in weather prediction (climate being the integral of weather) is adequately taken care of by the modelers?

Outside of the fact that you’re insisting that we can’t know or predict the effects of high CO2 without actually measuring it in the field, would you care to reconsider this claim about high CO2 data?

That’s a laugher. A link to paleoclimate data showing a past correlation between CO2 levels and temperature validates gridded models of the future? That’s now how model verification works.

And clearly such things as the En Nino and other such perturbations have been modeled in themselves … and predicted with some degree of accuracy. Why do you say the GC models don’t include this? be specific now.

You’re the one that says the GC models don’t include this. Out with it.

badlaw: zuch, while I normally avoid responding to you and your posts, …

You might best have followed your first instincts.

badlaw: I feel it’s necessary to tell you that you come off snide, sarcastic, and rude, and the fact that you cap off your posts with “cheers” doesn’t help matters.

It’s truly amasing what annoys some people. And sarcasm has a legitimate function. Really.

badlaw: I do think this site would be better off without you.

Tohzhe, tovarich. Did your post contribute anything useful?

Cheers,

John Moore:… the theorists had already published the “how” of cold fusion before the “what” was shown to be junk.

I know there were a couple articles, but all-in-all, most physicists I talked at the time were sceptical of these. You’d have noted that Fleishman and Pons got an Ig Nobel for their efforts; this is hardly the mark of tolerance for ‘error’. I suspect the few theoretical papers came out in an attempt to match up to the flawed experiments; I doubt they’d have gotten published otherwise.

John Moore: There are some climate scientists (AGW proponents) who have expressed concern because their models failed to predict the current trend. Saying it is not specific, when it invalidates your models, is pretty absurd.?

What “current trend”? Once again, cherry picking years does not a trend make. And the models recognise solar cycles but don’t attempt to predict deviations in such (as in the extended current solar lull). And how do the deviations “invalidate” the model? Such may indicate that the model is not complete, but that’s a far cry from “invalid”.

John Moore:

[zuch]: Don’t be a doofus here. This was in response to your denigration of modeling as a technique. I never said what you suggest here. All I said was that modeling is hardly something to be scorned, as you in fact did.

And don’t be such a toad. I never said modeling was something to be scorned — I said that future climate prediction models were not credible. I hope you can understand the difference.

Yes. You said that certain models (whose outcomes you apparently don’t agree with) should be scorned. Scorned to the extend that “nobody with any sense” should believe them. Seeing as they are predictive models, you either have no results to show that they are unbelievable, or you would have to apply these models post hoc to existing data to show that they do not predict what we’ve already observed. If the latter, please show your work.

John Moore:

[zuch]: As I’m sure you know, the models used to predict weather a couple of weeks in advance are far different from the models used to predict GW in decades ahead. Right?…

They are, and they aren’t. They use the same basic atmospheric modeling approaches (except for the ocean coupled climate models which add in some others). One difference that you obviously missed is that the weather models are used for prediction, while the global models do NOT. At best, they attempt to measure sensitivity. Chaos guarantees that you cannot use finite element models of the atmosphere for prediction decades in the future.

The global models aren’t predictive?!?!? Of course, they do measure sensitivity to various perturbations as well.

As for “chaos”, you’ve been reading a bit too much fluff. It is true that chaotic behaviour does make it harder and harder to extend FEM models of weather farther and farther into the future at the sub-macro level, but to invalidate the global models, you’d have to establish that such systems are beset by chaotic behaviour as well … and that this chaotic behaviour cannot be quantified and predicted (one of the more interesting results in chaos theory is that what looks totally unpredictable at first blush often shows a quite startling order). Have you done this? If so, where it it published?

John Moore: There is NO experimental data for an atmosphere with high CO2. None.

Outside of the fact that you’re insisting that we can’t know or predict the effects of high CO2 without actually measuring it in the field, would you care to reconsider this claim about high CO2 data?

John Moore: But respond to the threads of logic mixed into it. I don’t know the models are wrong.

Yet you say they are. You say (falsely) “nobody with any sense” believes them.

John Moore: I know that, since the models do not take these things into account, and because science (not just me) doesn’t understand these oscillations (and lots of other large scale, long term things) well enough, that the models are necessarily suspect.

Please explain how the models don’t take “these things” into account. At the very least, such things are incorporated into the variability of the model predictions (based on the variability of the historic data). Many models look explicitly for oscillations or other factors in the ANOVA of the historical data, even if they don’t explicitly model the mechanics of solar oscillations. And clearly such things as the En Nino and other such perturbations have been modeled in themselves … and predicted with some degree of accuracy. Why do you say the GC models don’t include this? be specific now.

John Moore: If you claim to know how to predict, lets say, the PDO, then out with it. If you claim to know its effect on model accuracy, and even more, on model calibration, out with it.

You’re the one that says the GC models don’t include this. Out with it.

As it turned out, the experiments were bunk, but the theorists had already published the “how” of cold fusion before the “what” was shown to be junk.

Actually, the Jones experiment was not bunk – it just failed to work out in replication attempts – but Jones was very honest about the whole thing. The Pons/Fleischmann experiment used abominable technique (I’m not an electro-chemist, but it didn’t take me long to see a few major holes in it – open cell calorimetry and rapid replacement of D2O with H2O through normal evaporation) and their paper committed the sin of generating it’s main claim (high levels of energy gain) by dividing by the difference of two unreliable variables.

“Cold fusion” had no “politic[al]” implications?!?!? And I don’t remember a “raft” of such. I’d say that excrement tends to float to the top, so that may have been what you saw, but I noticed no such thing in the real literature.

Cold fusion didn’t last long enough to have the sort of political chaos that is happening with AGW. I’m sorry you missed the articles, but they were in theoretical physics journals. As it turned out, the experiments were bunk, but the theorists had already published the “how” of cold fusion before the “what” was shown to be junk.

Huh? What “unjustifiable biasing of data sets”? What “cherry picking of data”? Anything like the “cherry picking of data” of the people that claim that the last 8 years have been getting cooler (even though anti-AGW scientists have said that this “trend” is not significant [if it even exists])

The “real scientists?” There are some climate scientists (AGW proponents) who have expressed concern because their models failed to predict the current trend. Saying it is not specific, when it invalidates your models, is pretty absurd.?

Don’t be a doofus here. This was in response to your denigration of modeling as a technique. I never said what you suggest here. All I said was that modeling is hardly something to be scorned, as you in fact did.

And don’t be such a toad. I never said modeling was something to be scorned – I said that future climate prediction models were not credible. I hope you can understand the difference.

As I’m sure you know, the models used to predict weather a couple of weeks in advance are far different from the models used to predict GW in decades ahead. Right?…

They are, and they aren’t. They use the same basic atmospheric modeling approaches (except for the ocean coupled climate models which add in some others). One difference that you obviously missed is that the weather models are used for prediction, while the global models do NOT. At best, they attempt to measure sensitivity. Chaos guarantees that you cannot use finite element models of the atmosphere for prediction decades in the future.

John Moore:
The differencis include: the GCM’s are modeling a far more complex and less well understood system than those you mention; the GCM’s cannot be calibrated for high CO2, since there is no experimental data;

Huh?!?!? Do you really think that the models can’t account for at least the known physical characteristics of high CO2 concentrations?!?!? And what makes you think there’s no experimental data? Do you think that the models rely on historical environmental data alone (and exist independent of any laboratory data or even known physics)?

Anyone who has worked with atmospheric physics knows that lab experiments (which establish basic physical relationships) are simply not where you test complex atmospheric interactions (which is to say, any real atmospheric phenomenon). There is NO experimental data for an atmosphere with high CO2. None. Unless you have a time machine.

John Moore:
… the GCM’s do not account for many known (but not well understood) phenomena such as ENSO, PDO, NAO and others; the GCM’s cannot handle carbon budgets, because we don’t know the carbon processes well enough.

Argumentum ad ignorantiam, eh? You know the models are wrong because you don’t know enough about these things?!?!? And how can you say the models don’t account for this kind of stuff? Examples, please? I’d note that oscillations are just that. Do you say that the oscillations will cease in the future under more extreme conditions? Do you say they will counteract the overall GW? If so, out with your data. Otherwise, why should we pay attention to you when you say that the effects of these have not been taken into account … when you don’t know WTF you’re talking about YOURSELF!!!!.

Argumentum ad hominem.

Your last paragraph is ranting. But respond to the threads of logic mixed into it. I don’t know the models are wrong. I know that, since the models do not take these things into account, and because science (not just me) doesn’t understand these oscillations (and lots of other large scale, long term things) well enough, that the models are necessarily suspect. If they are right, it would be because even a military clock is right once a day. If you claim to know how to predict, lets say, the PDO, then out with it. If you claim to know its effect on model accuracy, and even more, on model calibration, out with it. If you know that these oscillations will integrate out to zero effect, perhaps you should lay that evidence out while you are at it. Oh, and the same applies to carbon budgets, if that is what you are ranting about. Or, maybe you’d like to take your hand at predicting the CO2 sensitivity of cloud droplet size contribution to earth’s albedo, since you’re so confident. Or maybe you would just admit that the science is in its infancy, that the all important feedbacks are not well understood, and that the “science is settled” is about as accurate as it was when “physics is finished” was bandied about in the late 19th century!

But you don’t know that, because NOBODY knows that.

What part of “It’s all lies” don’t you get?

Why do you still think AGW is real, and this is only a marginal issue?

The commenter who wrote that just because some doctors are unethical doesn’t mean he’s going to go to a shaman—in this case, it’s YOUR doctor who has been proven unethical and while that doesn’t mean go to a shaman it does mean throw out everything he’s told you and find a better doctor.

Let me make this simple enough for even a lawyer:

We don’t know ANYTHING trustworthy about long-term climate forecasting, except anecdotal information, and we don’t have a good context in which to place those anecdotes.

The data is all bad and corrupted. We have no way to differentiate any good data from the bad, so we have to assume it’s all unreliable until it can be reviewed and validated.

The models never worked very well and now we see the problem is even worse than that, the people who are supposed to run them can’t even get them to work, let alone produce results of any worth. Of course, since the input data isn’t reliable and the modelers won’t share and explain their code, we already suspected this. We have to assume all the modeling is wortrhless, and we need to validate the models at the same time as the data, so at some future date good data can be run through validated models.

The “consensus” has been produced by greed for research funds and status, and enforced through intimidation.

These people (the climate scientists et al, who are implicated) want to rearrange the world economy for the next century and beyond and destroy trillions of dollars of economic value, in some cases while taking advantage and enriching themselves as they impoverish others, and have been lying to you in order to get this accomplished.

Doesn’t that BOTHER you?

What do you folks not understand about all this?

John Moore: That would be a huge statistical unlikelihood, given the history of other, less politicized branches of science. For example, when cold fusion first appeared, there were a raft of peer reviewed papers in normal journals giving various theories to explain it — even though the whole thing was strongly against consensus.

“Cold fusion” had no “politic[al]” implications?!?!? And I don’t remember a “raft” of such. I’d say that excrement tends to float to the top, so that may have been what you saw, but I noticed no such thing in the real literature.

John Moore:

[zuch]: How so? And what “fraud”?

The unjustifiable biasing of data sets, and the cherry picking of data shown both in the software code and the emails.

Huh? What “unjustifiable biasing of data sets”? What “cherry picking of data”? Anything like the “cherry picking of data” of the people that claim that the last 8 years have been getting cooler (even though anti-AGW scientists have said that this “trend” is not significant [if it even exists])?

John Moore:

[zuch]: Modeling was and is used to predict nuclear explosions. It’s immensely successful; even so for the modeling of the Pu-239 bomb (Fat Man) done by calculators and slide rule. And where do you get this “nobody with any sense”?

That’s pretty rich. Modeling does X, so modeling in field Y must be reliable!

Don’t be a doofus here. This was in response to your denigration of modeling as a technique. I never said what you suggest here. All I said was that modeling is hardly something to be scorned, as you in fact did.

John Moore: If you know anything about climate models and GCM’s, then you could understand my statement. GCM’s are indeed useful — for helping forecast weather. They are grossly less than credible for giving climate forecasts far into the future, and the scientists working with them know that and discuss some of the “embarassing” lapses. 

As I’m sure you know, the models used to predict weather a couple of weeks in advance are far different from the models used to predict GW in decades ahead. Right?….

John Moore: As a simple example, they failed to predict the recent global cooling. 

What recent “global cooling”?

John Moore:
The differencis include: the GCM’s are modeling a far more complex and less well understood system than those you mention; the GCM’s cannot be calibrated for high CO2, since there is no experimental data;

Huh?!?!? Do you really think that the models can’t account for at least the known physical characteristics of high CO2 concentrations?!?!? And what makes you think there’s no experimental data? Do you think that the models rely on historical environmental data alone (and exist independent of any laboratory data or even known physics)?

John Moore:
… the GCM’s do not account for many known (but not well understood) phenomena such as ENSO, PDO, NAO and others; the GCM’s cannot handle carbon budgets, because we don’t know the carbon processes well enough.

Argumentum ad ignorantiam, eh? You know the models are wrong because you don’t know enough about these things?!?!? And how can you say the models don’t account for this kind of stuff? Examples, please? I’d note that oscillations are just that. Do you say that the oscillations will cease in the future under more extreme conditions? Do you say they will counteract the overall GW? If so, out with your data. Otherwise, why should we pay attention to you when you say that the effects of these have not been taken into account … when you don’t know WTF you’re talking about YOURSELF!!!!.

Cheers,

There’s an assumption here that needs to be addressed: That any such studies that allegedly show no AGW are worth publishing. They may well be just mostly fluff and “crap”.

That would be a huge statistical unlikelihood, given the history of other, less politicized branches of science. For example, when cold fusion first appeared, there were a raft of peer reviewed papers in normal journals giving various theories to explain it – even though the whole thing was strongly against consensus. In that case, the hypotheses were testable in a lab, so science won the day. The idea that there are no skeptical papers of merit is so totally absurd as to be laughable.

How so? And what “fraud”?

The unjustifiable biasing of data sets, and the cherry picking of data shown both in the software code and the emails.

Modeling was and is used to predict nuclear explosions. It’s immensely successful; even so for the modeling of the Pu-239 bomb (Fat Man) done by calculators and slide rule. And where do you get this “nobody with any sense”?

That’s pretty rich. Modeling does X, so modeling in field Y must be reliable!

If you know anything about climate models and GCM’s, then you could understand my statement. GCM’s are indeed useful – for helping forecast weather. They are grossly less than credible for giving climate forecasts far into the future, and the scientists working with them know that and discuss some of the “embarassing” lapses.

As a simple example, they failed to predict the recent global cooling.

Finally, to get into modeling a bit… the kind you mention are finite element (or finite difference) models. So are GCM’s. The differencis include: the GCM’s are modeling a far more complex and less well understood system than those you mention; the GCM’s cannot be calibrated for high CO2, since there is no experimental data; the GCM’s are many orders of magnitude too coarse in their spatial and temporal resolution to resolve processes important for what they are modeling; the GCM’s do not account for many known (but not well understood) phenomena such as ENSO, PDO, NAO and others; the GCM’s cannot handle carbon budgets, because we don’t know the carbon processes well enough. That’s a few of the reasons no rational person would believe the model based climate predictions for far into the future.

BTW, these same models are used for weather forecasting. Here’s an example of yesterday’s model usage from NWS Phoenix AZ – note the uncertainties for the very short term:

QUITE A BIT OF DISAGREEMENT BETWEEN MODELS ON THE TIMING AND
TRAJECTORY OF THE TROUGH AND UPPER LEVEL LOW AS THEY SWING ACROSS
SOUTHERN CALIFORNIA. THE GFS AND ECMWF BEGIN TO DEVIATE AFTER 12Z ON
SATURDAY. THE ECMWF DEVELOPS A MUCH DEEPER UPPER LOW AND AND SWINGS
IT ACROSS SOUTHERN ARIZONA. THE LOW DEVELOPED BY THE GFS IS LESS
INTENSE…THOUGH THE MODEL DIGS IT MUCH FURTHER SOUTH DOWN THE
WESTERN BAJA COAST…BEFORE KICKING IT OUT TO THE EAST MONDAY
MORNING. THE END RESULT IS THAT THE GFS TROUGH AXIS IS LATER TO PUSH
ACROSS THE SOUTHWEST THAN THE ECMWF.

GFS and ECMWF are two of the most commonly used weather GCMs.

John Curran: If there is information in the data sets that the contributors don’t want released, redact that data.

Ummmm … the RealClimate page you linked to says:

“… The vast majority of the data in the HadCRU records is publicly available from GHCN.”

Isn’t that what you’re asking for?

Cheers,

John Moore: The problem is that the total suppression of skeptical studies. Just because the pro-AGW folks nit-pick over each others data doesn’t mean that the skeptics are not being suppressed. The CRU emails are clear evidence of that suppression.

There’s an assumption here that needs to be addressed: That any such studies that allegedly show no AGW are worth publishing. They may well be just mostly fluff and “crap”.

John Moore: What makes the CRU fraud so important is that recent paleoclimatic data is the final leg left standing in the AGW crusade.

How so? And what “fraud”?

John Moore: Modeling was and is used to produce alarming forecasts, but nobody with any sense believes these models.

Modeling was and is used to predict nuclear explosions. It’s immensely successful; even so for the modeling of the Pu-239 bomb (Fat Man) done by calculators and slide rule. And where do you get this “nobody with any sense”?

John Moore: When you also realize that the CRU data is at the heart of so much of the paleoclimatic case, it’s even more significant.

Huh? How so? Please explain.

Cheers,

But I think that you have a more difficult case to make to say that because essentially all studies are showing some warming, that this is because of fraud, and not instead because in fact the warming is a very solid and significant fact. Amongst other things, the studies are being done by many different scientists in a number of different ways.

The problem is that the total suppression of skeptical studies. Just because the pro-AGW folks nit-pick over each others data doesn’t mean that the skeptics are not being suppressed. The CRU emails are clear evidence of that suppression.

Furthermore, most studies in the field are not about verifying past warming or showing future warming – they are about the myriad of technical details involved in such a complex subject. Hence the “weight” of studies is hardly a satisfying argument.

What makes the CRU fraud so important is that recent paleoclimatic data is the final leg left standing in the AGW crusade. Modeling was and is used to produce alarming forecasts, but nobody with any sense believes these models. OTOH, records of past warming, if they meet certain criteria, are far more suggestive of the CO2->AGW hypothesis (although they are subject to criticism on short term trend basis). When you also realize that the CRU data is at the heart of so much of the paleoclimatic case, it’s even more significant.
It is hardly surprising, therefore, that this data is the most manipulated and most protected. Without it, the AGW alarmist case crumbles.

And guess what, the number of crumbs on the plate is starting to get bigger than the AGW pie.

Hugh: I’ve especially skeptical when I read global warming advocates claiming that there have been some 3000 scientific studies done and they all conclude that AGW is real. Do you have any idea how unlikely it is that 3000 studies will reach the same conclusion? It’s about the same odds as a banana republic dictator actually receiving 99.9% of the popular vote.

This would be true if all studies were published, and in fact, all reached the same precise conclusion. That’s not true, though.

In fact, “Sir” Cyril Burt was unmasked in his fraud because his data were just too damn good: His correlation coefficients kept coming up identical to many decimal places for new sets of data.

But I think that you have a more difficult case to make to say that because essentially all studies are showing some warming, that this is because of fraud, and not instead because in fact the warming is a very solid and significant fact. Amongst other things, the studies are being done by many different scientists in a number of different ways.

I wouldn’t be surprised in the least by a study that said that pennies dropped fall down rather than up, and that this happens in essentially all studies that were ever done of the effect. That’s not suspicious … and you might consider whether the strong consensus on warming is A similar phenomenon.

Cheers,

It’s like a composer pointing to a piano and saying, “that’s my data, reconstruct my symphony.”

On balance, therefore, I still think that global warming exists and is a genuinely serious problem.

For Heaven’s sake, why?

I mean, seriously – why?

Cheers,

http://www.realclimate.org/

“CRU data accessibility. From the date of the first FOI request to CRU (in 2007), it has been made abundantly clear that the main impediment to releasing the whole CRU archive is the small % of it that was given to CRU on the understanding it wouldn’t be passed on to third parties. Those restrictions are in place because of the originating organisations (the various National Met. Services) around the world and are not CRU’s to break. As of Nov 13, the response to the umpteenth FOI request for the same data met with exactly the same response. This is an unfortunate situation, and pressure should be brought to bear on the National Met Services to release CRU from that obligation. It is not however the fault of CRU. The vast majority of the data in the HadCRU records is publicly available from GHCN.”

If there is information in the data sets that the contributors don’t want released, redact that data. Redaction is part of the FOIA process. I have a very hard time believing that temperature records can be anything but public domain information.

I wasn’t dissing error bars in general, Jim, and some points made about their relevance further upthread were well taken.

The graph I linked to illustrates very well when error bars are relevant by being a glaring example of when they are not relevant – in this case because a more sensitive method of measurement has supplanted a less sensitive one, as well as because the smoothed trend overwhelms potential error bar distortion.

I’d have thought that was obvious from the graph. I’ll respect your intelligence by venturing that you didn’t bother to follow the link to it.

AlanDownunder: This will change no minds.Neither, even, will this graph. Someone will rabbit on about error bars or something … anything.

If you’re gonna diss error bars, you should learn a little about them first -

http://strata-sphere.com/blog/index.php/archives/11523

geokstr says:

(My apologies if I’m getting you mixed up with another commenter. If I got it right, apology withdrawn.)

Apology accepted.

Ideology ordains that this graph is fraudulent. “Proof” to follow.

The models aren’t killed by this, but they are already on thin ice, so to speak.

If this were not something so important, I’d more or less give it a pass – scientists are human too. But it is terribly important, and hence this stuff needs to be precise. The reviewers of the papers of these folks need to be publicly exposed for their failure to demand better disclosure. The editors of the journals need to be challenged.

We can hope that this will force paleoclimatologists and scientists in lots of other fields to be a whole lot more careful with their data and their processing of it, and their “peer reviewers” to be a whole lot more demanding. In fact, hopefully this will serve as a wakeup to big-science that in this modern age, where they can’t record their data in bound lab books, they need to be as careful with it as if they were doing so. They need to get the message that work will not be published unless the data, the meta-data and the software related to it is publicly available on the internet.

Just as the internet now challenges the main stream media and other institutions, it should be available as a medium to challenge scientific results. The strongly held idea by many scientists that they are the priests in the temple, and nobody else can understand the mysteries, needs to go.

There are some common grounds between AGW and socialism.

Socialist believe that society’s ills can be managed by depriving many of some measure of liberty and property to benefit a few. It is self-delusional arrogance that we can craft a solution to social ills that will not diminish the personal responsibility of the targets nor diminish the productivity of the victims.

Since rational beings will modify their behavior in response to such actions, many will not work hard to contribute to the “great storehouse”, if they can take from the storehouse without working.

Both derive from an arrogance of mind that maintains that “I know best how to control other people and how to spend their money for their benefit.” As with all forms of arrogance, those that disagree simply are not as intelligent and informed.

That said, I don’t think we have anywhere close to sufficient proof of such bias to simply discount the dominant scientific view of global warming.

Important to note that models used to predict AGW cannot explain the relative decline for the past decade. Coupled with obvious attempts to stifle dissenting opinions, this is a colossal indication that intellectual dishonesty permeates this endeavor. The public should demand impartial adjudication of this prior to expending another dime.

If you live for two more decades, you will have an opportunity to see this type of crusader arrogance reborn in some other guise. There will always be some group shouting that “the sky is falling” and demanding immediate action. Perhaps it will be killer asteroids or alien invasions next.

Of all the work done on AGW, define “work”.
I’m getting the impression that it’s like an inverted pyamid, all this “work” based on a small amount of the basic data, much of which has been compromised.

There are several areas of work. Here are some major ones, only one of which has been seriously damaged by the scandal:

1) Paleoclimatology and CO2 – the work to determine past global temperature, CO2 levels, and their relationship. This has been clobbered by the scandal.

2) Modeling – this is an attempt to predict future climate – specifically temperature in this case. The scandal only impacts this if it affects model calibration. Modeling has major problems in this realm, however: the phenomena are extremely difficult to model – maybe impossible; the models cannot be calibrated; the models are subject to cherry picking of parameters – conscious or far more likely, unlikely. Most work in this area involves the creation of parameterization for those phenomena which cannot be directly modeled (almost all of them, in other words), and the calibration of those parameters.

It is the modeling which produces the alarming forecasts, because basic physics cannot (it produces 1.2C/doubling). It is also the modeling which is the least reliable (if it means anything at all). The weakness of the modeling is why the paleoclimatic record has become so critical to AGW proponents, and why the last few decades especially are so emphasized (and, we now know, subject to cheating).

3) Instrumentation – the development and deployment of instruments which measure various climate variables – CO2 concentration (easy), ocean temperature and energy content, the earth’s albedo (hard), global temperature (hard), etc. Direct global temperature measurement has only been available for the last couple of decades – by satellites – and contradicts the surface warming records that produce the hockey sticks (leading to very strong attacks on the satellite researchers). Most other parameters are also measured for only very recent times (albedo, ocean energy storage).

4) Derivative work – this is work which does not address the prediction of global temperature, but rather the consequences of it. There are huge numbers of papers on this subject in every field imaginable. I did a google scholar word search and found some amazing (if not terribly precise) results – at http://www.tinyvital.com/blog/2009/03/15/climate-change-gold-mine-for-all-kinds-of-scientists/. This derivative research shows one of the strong financial drivers for AGW – it produces funding for researchers in every field of science and quasi(pseduo?) science (latter category includes a lot of social “science.” etc).

246.AlanDownunder says:
This will change no minds.

Neither, even, will this graph. Someone will rabbit on about error bars or something … anything.

And why should they? When is the last time that you were open enough to let someone on the right change your mind about, well, just about anything? And aren’t you the “Marxist economist”, whatever that is? (My apologies if I’m getting you mixed up with another commenter. If I got it right, apology withdrawn.)